huggingface
train_controlnet
from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler from diffusers.utils import load_image import torch
base_model_path = "stable-diffusion-v1-5/stable-diffusion-v1-5" controlnet_path = "./output/checkpoint-12500/controlnet/"
controlnet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=torch.float16) pipe = StableDiffusionControlNetPipeline.from_pretrained( base_model_path, controlnet=controlnet, torch_dtype=torch.float16 )
speed up diffusion process with faster scheduler and memory optimization
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
remove following line if xformers is not installed or when using Torch 2.0.
pipe.enable_xformers_memory_efficient_attention()
memory optimization.
pipe.enable_model_cpu_offload()
control_image = load_image("./conditioning_image_1.png") prompt = "pale golden rod circle with old lace background"
generate image
generator = torch.manual_seed(0) image = pipe( prompt, num_inference_steps=20, generator=generator, image=control_image ).images[0] image.save("./output.png")
Error when using the official inference script RuntimeError: Data processing error: CAS service error : Reqwest Error: HTTP status client error (401 Unauthorized), domain: https://cas-server.xethub.hf.co/reconstructions/3e6084a7831fd989ab9e7a6a88745fce55823b69b6ea6832ff6c5cc08fee958f
